package com.len.util;

import java.awt.Color;
import java.awt.Graphics2D;
import java.awt.image.BufferedImage;
import java.awt.image.DataBufferByte;
import java.io.BufferedOutputStream;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.OutputStream;
 
/**
 * Class AnimatedGifEncoder - Encodes a GIF file consisting of one or more
 * frames.
 * 
 * <pre>
 *  Example:
 *     AnimatedGifEncoder e = new AnimatedGifEncoder();
 *     e.start(outputFileName);
 *     e.setDelay(1000);   // 1 frame per sec
 *     e.addFrame(image1);
 *     e.addFrame(image2);
 *     e.finish();
 * </pre>
 * 
 * No copyright asserted on the source code of this class. May be used for any
 * purpose, however, refer to the Unisys LZW patent for restrictions on use of
 * the associated LZWEncoder class. Please forward any corrections to
 * kweiner@fmsware.com.
 * 
 * @author Kevin Weiner, FM Software
 * @version 1.03 November 2003
 * 
 */
 
public class AnimatedGifEncoder {
 
  protected int width; // image size
 
  protected int height;
 
  protected Color transparent = null; // transparent color if given
 
  protected int transIndex; // transparent index in color table
 
  protected int repeat = -1; // no repeat
 
  protected int delay = 0; // frame delay (hundredths)
 
  protected boolean started = false; // ready to output frames
 
  protected OutputStream out;
 
  protected BufferedImage image; // current frame
 
  protected byte[] pixels; // BGR byte array from frame
 
  protected byte[] indexedPixels; // converted frame indexed to palette
 
  protected int colorDepth; // number of bit planes
 
  protected byte[] colorTab; // RGB palette
 
  protected boolean[] usedEntry = new boolean[256]; // active palette entries
 
  protected int palSize = 7; // color table size (bits-1)
 
  protected int dispose = -1; // disposal code (-1 = use default)
 
  protected boolean closeStream = false; // close stream when finished
 
  protected boolean firstFrame = true;
 
  protected boolean sizeSet = false; // if false, get size from first frame
 
  protected int sample = 10; // default sample interval for quantizer
 
  /**
   * Sets the delay time between each frame, or changes it for subsequent frames
   * (applies to last frame added).
   * 
   * @param ms
   *          int delay time in milliseconds
   */
  public void setDelay(int ms) {
    delay = Math.round(ms / 10.0f);
  }
 
  /**
   * Sets the GIF frame disposal code for the last added frame and any
   * subsequent frames. Default is 0 if no transparent color has been set,
   * otherwise 2.
   * 
   * @param code
   *          int disposal code.
   */
  public void setDispose(int code) {
    if (code >= 0) {
      dispose = code;
    }
  }
 
  /**
   * Sets the number of times the set of GIF frames should be played. Default is
   * 1; 0 means play indefinitely. Must be invoked before the first image is
   * added.
   * 
   * @param iter
   *          int number of iterations.
   * @return
   */
  public void setRepeat(int iter) {
    if (iter >= 0) {
      repeat = iter;
    }
  }
 
  /**
   * Sets the transparent color for the last added frame and any subsequent
   * frames. Since all colors are subject to modification in the quantization
   * process, the color in the final palette for each frame closest to the given
   * color becomes the transparent color for that frame. May be set to null to
   * indicate no transparent color.
   * 
   * @param c
   *          Color to be treated as transparent on display.
   */
  public void setTransparent(Color c) {
    transparent = c;
  }
 
  /**
   * Adds next GIF frame. The frame is not written immediately, but is actually
   * deferred until the next frame is received so that timing data can be
   * inserted. Invoking <code>finish()</code> flushes all frames. If
   * <code>setSize</code> was not invoked, the size of the first image is used
   * for all subsequent frames.
   * 
   * @param im
   *          BufferedImage containing frame to write.
   * @return true if successful.
   */
  public boolean addFrame(BufferedImage im) {
    if ((im == null) || !started) {
      return false;
    }
    boolean ok = true;
    try {
      if (!sizeSet) {
        // use first frame's size
        setSize(im.getWidth(), im.getHeight());
      }
      image = im;
      getImagePixels(); // convert to correct format if necessary
      analyzePixels(); // build color table & map pixels
      if (firstFrame) {
        writeLSD(); // logical screen descriptior
        writePalette(); // global color table
        if (repeat >= 0) {
          // use NS app extension to indicate reps
          writeNetscapeExt();
        }
      }
      writeGraphicCtrlExt(); // write graphic control extension
      writeImageDesc(); // image descriptor
      if (!firstFrame) {
        writePalette(); // local color table
      }
      writePixels(); // encode and write pixel data
      firstFrame = false;
    } catch (IOException e) {
      ok = false;
    }
 
    return ok;
  }
 
  /**
   * Flushes any pending data and closes output file. If writing to an
   * OutputStream, the stream is not closed.
   */
  public boolean finish() {
    if (!started)
      return false;
    boolean ok = true;
    started = false;
    try {
      out.write(0x3b); // gif trailer
      out.flush();
      if (closeStream) {
        out.close();
      }
    } catch (IOException e) {
      ok = false;
    }
 
    // reset for subsequent use
    transIndex = 0;
    out = null;
    image = null;
    pixels = null;
    indexedPixels = null;
    colorTab = null;
    closeStream = false;
    firstFrame = true;
 
    return ok;
  }
 
  /**
   * Sets frame rate in frames per second. Equivalent to
   * <code>setDelay(1000/fps)</code>.
   * 
   * @param fps
   *          float frame rate (frames per second)
   */
  public void setFrameRate(float fps) {
    if (fps != 0f) {
      delay = Math.round(100f / fps);
    }
  }
 
  /**
   * Sets quality of color quantization (conversion of images to the maximum 256
   * colors allowed by the GIF specification). Lower values (minimum = 1)
   * produce better colors, but slow processing significantly. 10 is the
   * default, and produces good color mapping at reasonable speeds. Values
   * greater than 20 do not yield significant improvements in speed.
   * 
   * @param quality
   *          int greater than 0.
   * @return
   */
  public void setQuality(int quality) {
    if (quality < 1)
      quality = 1;
    sample = quality;
  }
 
  /**
   * Sets the GIF frame size. The default size is the size of the first frame
   * added if this method is not invoked.
   * 
   * @param w
   *          int frame width.
   * @param h
   *          int frame width.
   */
  public void setSize(int w, int h) {
    if (started && !firstFrame)
      return;
    width = w;
    height = h;
    if (width < 1)
      width = 320;
    if (height < 1)
      height = 240;
    sizeSet = true;
  }
 
  /**
   * Initiates GIF file creation on the given stream. The stream is not closed
   * automatically.
   * 
   * @param os
   *          OutputStream on which GIF images are written.
   * @return false if initial write failed.
   */
  public boolean start(OutputStream os) {
    if (os == null)
      return false;
    boolean ok = true;
    closeStream = false;
    out = os;
    try {
      writeString("GIF89a"); // header
    } catch (IOException e) {
      ok = false;
    }
    return started = ok;
  }
 
  /**
   * Initiates writing of a GIF file with the specified name.
   * 
   * @param file
   *          String containing output file name.
   * @return false if open or initial write failed.
   */
  public boolean start(String file) {
    boolean ok = true;
    try {
      out = new BufferedOutputStream(new FileOutputStream(file));
      ok = start(out);
      closeStream = true;
    } catch (IOException e) {
      ok = false;
    }
    return started = ok;
  }
 
  /**
   * Analyzes image colors and creates color map.
   */
  protected void analyzePixels() {
    int len = pixels.length;
    int nPix = len / 3;
    indexedPixels = new byte[nPix];
    NeuQuant nq = new NeuQuant(pixels, len, sample);
    // initialize quantizer
    colorTab = nq.process(); // create reduced palette
    // convert map from BGR to RGB
    for (int i = 0; i < colorTab.length; i += 3) {
      byte temp = colorTab[i];
      colorTab[i] = colorTab[i + 2];
      colorTab[i + 2] = temp;
      usedEntry[i / 3] = false;
    }
    // map image pixels to new palette
    int k = 0;
    for (int i = 0; i < nPix; i++) {
      int index = nq.map(pixels[k++] & 0xff, pixels[k++] & 0xff, pixels[k++] & 0xff);
      usedEntry[index] = true;
      indexedPixels[i] = (byte) index;
    }
    pixels = null;
    colorDepth = 8;
    palSize = 7;
    // get closest match to transparent color if specified
    if (transparent != null) {
      transIndex = findClosest(transparent);
    }
  }
 
  /**
   * Returns index of palette color closest to c
   * 
   */
  protected int findClosest(Color c) {
    if (colorTab == null)
      return -1;
    int r = c.getRed();
    int g = c.getGreen();
    int b = c.getBlue();
    int minpos = 0;
    int dmin = 256 * 256 * 256;
    int len = colorTab.length;
    for (int i = 0; i < len;) {
      int dr = r - (colorTab[i++] & 0xff);
      int dg = g - (colorTab[i++] & 0xff);
      int db = b - (colorTab[i] & 0xff);
      int d = dr * dr + dg * dg + db * db;
      int index = i / 3;
      if (usedEntry[index] && (d < dmin)) {
        dmin = d;
        minpos = index;
      }
      i++;
    }
    return minpos;
  }
 
  /**
   * Extracts image pixels into byte array "pixels"
   */
  protected void getImagePixels() {
    int w = image.getWidth();
    int h = image.getHeight();
    int type = image.getType();
    if ((w != width) || (h != height) || (type != BufferedImage.TYPE_3BYTE_BGR)) {
      // create new image with right size/format
      BufferedImage temp = new BufferedImage(width, height, BufferedImage.TYPE_3BYTE_BGR);
      Graphics2D g = temp.createGraphics();
      g.drawImage(image, 0, 0, null);
      image = temp;
    }
    pixels = ((DataBufferByte) image.getRaster().getDataBuffer()).getData();
  }
 
  /**
   * Writes Graphic Control Extension
   */
  protected void writeGraphicCtrlExt() throws IOException {
    out.write(0x21); // extension introducer
    out.write(0xf9); // GCE label
    out.write(4); // data block size
    int transp, disp;
    if (transparent == null) {
      transp = 0;
      disp = 0; // dispose = no action
    } else {
      transp = 1;
      disp = 2; // force clear if using transparent color
    }
    if (dispose >= 0) {
      disp = dispose & 7; // user override
    }
    disp <<= 2;
 
    // packed fields
    out.write(0 | // 1:3 reserved
        disp | // 4:6 disposal
        0 | // 7 user input - 0 = none
        transp); // 8 transparency flag
 
    writeShort(delay); // delay x 1/100 sec
    out.write(transIndex); // transparent color index
    out.write(0); // block terminator
  }
 
  /**
   * Writes Image Descriptor
   */
  protected void writeImageDesc() throws IOException {
    out.write(0x2c); // image separator
    writeShort(0); // image position x,y = 0,0
    writeShort(0);
    writeShort(width); // image size
    writeShort(height);
    // packed fields
    if (firstFrame) {
      // no LCT - GCT is used for first (or only) frame
      out.write(0);
    } else {
      // specify normal LCT
      out.write(0x80 | // 1 local color table 1=yes
          0 | // 2 interlace - 0=no
          0 | // 3 sorted - 0=no
          0 | // 4-5 reserved
          palSize); // 6-8 size of color table
    }
  }
 
  /**
   * Writes Logical Screen Descriptor
   */
  protected void writeLSD() throws IOException {
    // logical screen size
    writeShort(width);
    writeShort(height);
    // packed fields
    out.write((0x80 | // 1 : global color table flag = 1 (gct used)
        0x70 | // 2-4 : color resolution = 7
        0x00 | // 5 : gct sort flag = 0
        palSize)); // 6-8 : gct size
 
    out.write(0); // background color index
    out.write(0); // pixel aspect ratio - assume 1:1
  }
 
  /**
   * Writes Netscape application extension to define repeat count.
   */
  protected void writeNetscapeExt() throws IOException {
    out.write(0x21); // extension introducer
    out.write(0xff); // app extension label
    out.write(11); // block size
    writeString("NETSCAPE" + "2.0"); // app id + auth code
    out.write(3); // sub-block size
    out.write(1); // loop sub-block id
    writeShort(repeat); // loop count (extra iterations, 0=repeat forever)
    out.write(0); // block terminator
  }
 
  /**
   * Writes color table
   */
  protected void writePalette() throws IOException {
    out.write(colorTab, 0, colorTab.length);
    int n = (3 * 256) - colorTab.length;
    for (int i = 0; i < n; i++) {
      out.write(0);
    }
  }
 
  /**
   * Encodes and writes pixel data
   */
  protected void writePixels() throws IOException {
    LZWEncoder encoder = new LZWEncoder(width, height, indexedPixels, colorDepth);
    encoder.encode(out);
  }
 
  /**
   * Write 16-bit value to output stream, LSB first
   */
  protected void writeShort(int value) throws IOException {
    out.write(value & 0xff);
    out.write((value >> 8) & 0xff);
  }
 
  /**
   * Writes string to output stream
   */
  protected void writeString(String s) throws IOException {
    for (int i = 0; i < s.length(); i++) {
      out.write((byte) s.charAt(i));
    }
  }
}
 
// 
// Adapted from Jef Poskanzer's Java port by way of J. M. G. Elliott.
// K Weiner 12/00
 
class LZWEncoder {
 
  private static final int EOF = -1;
 
  private int imgW, imgH;
 
  private byte[] pixAry;
 
  private int initCodeSize;
 
  private int remaining;
 
  private int curPixel;
 
  // GIFCOMPR.C - GIF Image compression routines
  //
  // Lempel-Ziv compression based on 'compress'. GIF modifications by
  // David Rowley (mgardi@watdcsu.waterloo.edu)
 
  // General DEFINEs
 
  static final int BITS = 12;
 
  static final int HSIZE = 5003; // 80% occupancy
 
  // GIF Image compression - modified 'compress'
  //
  // Based on: compress.c - File compression ala IEEE Computer, June 1984.
  //
  // By Authors: Spencer W. Thomas (decvax!harpo!utah-cs!utah-gr!thomas)
  // Jim McKie (decvax!mcvax!jim)
  // Steve Davies (decvax!vax135!petsd!peora!srd)
  // Ken Turkowski (decvax!decwrl!turtlevax!ken)
  // James A. Woods (decvax!ihnp4!ames!jaw)
  // Joe Orost (decvax!vax135!petsd!joe)
 
  int n_bits; // number of bits/code
 
  int maxbits = BITS; // user settable max # bits/code
 
  int maxcode; // maximum code, given n_bits
 
  int maxmaxcode = 1 << BITS; // should NEVER generate this code
 
  int[] htab = new int[HSIZE];
 
  int[] codetab = new int[HSIZE];
 
  int hsize = HSIZE; // for dynamic table sizing
 
  int free_ent = 0; // first unused entry
 
  // block compression parameters -- after all codes are used up,
  // and compression rate changes, start over.
  boolean clear_flg = false;
 
  // Algorithm: use open addressing double hashing (no chaining) on the
  // prefix code / next character combination. We do a variant of Knuth's
  // algorithm D (vol. 3, sec. 6.4) along with G. Knott's relatively-prime
  // secondary probe. Here, the modular division first probe is gives way
  // to a faster exclusive-or manipulation. Also do block compression with
  // an adaptive reset, whereby the code table is cleared when the compression
  // ratio decreases, but after the table fills. The variable-length output
  // codes are re-sized at this point, and a special CLEAR code is generated
  // for the decompressor. Late addition: construct the table according to
  // file size for noticeable speed improvement on small files. Please direct
  // questions about this implementation to ames!jaw.
 
  int g_init_bits;
 
  int ClearCode;
 
  int EOFCode;
 
  // output
  //
  // Output the given code.
  // Inputs:
  // code: A n_bits-bit integer. If == -1, then EOF. This assumes
  // that n_bits =< wordsize - 1.
  // Outputs:
  // Outputs code to the file.
  // Assumptions:
  // Chars are 8 bits long.
  // Algorithm:
  // Maintain a BITS character long buffer (so that 8 codes will
  // fit in it exactly). Use the VAX insv instruction to insert each
  // code in turn. When the buffer fills up empty it and start over.
 
  int cur_accum = 0;
 
  int cur_bits = 0;
 
  int masks[] = { 0x0000, 0x0001, 0x0003, 0x0007, 0x000F, 0x001F, 0x003F, 0x007F, 0x00FF, 0x01FF,
      0x03FF, 0x07FF, 0x0FFF, 0x1FFF, 0x3FFF, 0x7FFF, 0xFFFF };
 
  // Number of characters so far in this 'packet'
  int a_count;
 
  // Define the storage for the packet accumulator
  byte[] accum = new byte[256];
 
  // ----------------------------------------------------------------------------
  LZWEncoder(int width, int height, byte[] pixels, int color_depth) {
    imgW = width;
    imgH = height;
    pixAry = pixels;
    initCodeSize = Math.max(2, color_depth);
  }
 
  // Add a character to the end of the current packet, and if it is 254
  // characters, flush the packet to disk.
  void char_out(byte c, OutputStream outs) throws IOException {
    accum[a_count++] = c;
    if (a_count >= 254)
      flush_char(outs);
  }
 
  // Clear out the hash table
 
  // table clear for block compress
  void cl_block(OutputStream outs) throws IOException {
    cl_hash(hsize);
    free_ent = ClearCode + 2;
    clear_flg = true;
 
    output(ClearCode, outs);
  }
 
  // reset code table
  void cl_hash(int hsize) {
    for (int i = 0; i < hsize; ++i)
      htab[i] = -1;
  }
 
  void compress(int init_bits, OutputStream outs) throws IOException {
    int fcode;
    int i /* = 0 */;
    int c;
    int ent;
    int disp;
    int hsize_reg;
    int hshift;
 
    // Set up the globals: g_init_bits - initial number of bits
    g_init_bits = init_bits;
 
    // Set up the necessary values
    clear_flg = false;
    n_bits = g_init_bits;
    maxcode = MAXCODE(n_bits);
 
    ClearCode = 1 << (init_bits - 1);
    EOFCode = ClearCode + 1;
    free_ent = ClearCode + 2;
 
    a_count = 0; // clear packet
 
    ent = nextPixel();
 
    hshift = 0;
    for (fcode = hsize; fcode < 65536; fcode *= 2)
      ++hshift;
    hshift = 8 - hshift; // set hash code range bound
 
    hsize_reg = hsize;
    cl_hash(hsize_reg); // clear hash table
 
    output(ClearCode, outs);
 
    outer_loop: while ((c = nextPixel()) != EOF) {
      fcode = (c << maxbits) + ent;
      i = (c << hshift) ^ ent; // xor hashing
 
      if (htab[i] == fcode) {
        ent = codetab[i];
        continue;
      } else if (htab[i] >= 0) // non-empty slot
      {
        disp = hsize_reg - i; // secondary hash (after G. Knott)
        if (i == 0)
          disp = 1;
        do {
          if ((i -= disp) < 0)
            i += hsize_reg;
 
          if (htab[i] == fcode) {
            ent = codetab[i];
            continue outer_loop;
          }
        } while (htab[i] >= 0);
      }
      output(ent, outs);
      ent = c;
      if (free_ent < maxmaxcode) {
        codetab[i] = free_ent++; // code -> hashtable
        htab[i] = fcode;
      } else
        cl_block(outs);
    }
    // Put out the final code.
    output(ent, outs);
    output(EOFCode, outs);
  }
 
  // ----------------------------------------------------------------------------
  void encode(OutputStream os) throws IOException {
    os.write(initCodeSize); // write "initial code size" byte
 
    remaining = imgW * imgH; // reset navigation variables
    curPixel = 0;
 
    compress(initCodeSize + 1, os); // compress and write the pixel data
 
    os.write(0); // write block terminator
  }
 
  // Flush the packet to disk, and reset the accumulator
  void flush_char(OutputStream outs) throws IOException {
    if (a_count > 0) {
      outs.write(a_count);
      outs.write(accum, 0, a_count);
      a_count = 0;
    }
  }
 
  final int MAXCODE(int n_bits) {
    return (1 << n_bits) - 1;
  }
 
  // ----------------------------------------------------------------------------
  // Return the next pixel from the image
  // ----------------------------------------------------------------------------
  private int nextPixel() {
    if (remaining == 0)
      return EOF;
 
    --remaining;
 
    byte pix = pixAry[curPixel++];
 
    return pix & 0xff;
  }
 
  void output(int code, OutputStream outs) throws IOException {
    cur_accum &= masks[cur_bits];
 
    if (cur_bits > 0)
      cur_accum |= (code << cur_bits);
    else
      cur_accum = code;
 
    cur_bits += n_bits;
 
    while (cur_bits >= 8) {
      char_out((byte) (cur_accum & 0xff), outs);
      cur_accum >>= 8;
      cur_bits -= 8;
    }
 
    // If the next entry is going to be too big for the code size,
    // then increase it, if possible.
    if (free_ent > maxcode || clear_flg) {
      if (clear_flg) {
        maxcode = MAXCODE(n_bits = g_init_bits);
        clear_flg = false;
      } else {
        ++n_bits;
        if (n_bits == maxbits)
          maxcode = maxmaxcode;
        else
          maxcode = MAXCODE(n_bits);
      }
    }
 
    if (code == EOFCode) {
      // At EOF, write the rest of the buffer.
      while (cur_bits > 0) {
        char_out((byte) (cur_accum & 0xff), outs);
        cur_accum >>= 8;
        cur_bits -= 8;
      }
 
      flush_char(outs);
    }
  }
}
 
/*
 * NeuQuant Neural-Net Quantization Algorithm
 * ------------------------------------------
 * 
 * Copyright (c) 1994 Anthony Dekker
 * 
 * NEUQUANT Neural-Net quantization algorithm by Anthony Dekker, 1994. See
 * "Kohonen neural networks for optimal colour quantization" in "Network:
 * Computation in Neural Systems" Vol. 5 (1994) pp 351-367. for a discussion of
 * the algorithm.
 * 
 * Any party obtaining a copy of these files from the author, directly or
 * indirectly, is granted, free of charge, a full and unrestricted irrevocable,
 * world-wide, paid up, royalty-free, nonexclusive right and license to deal in
 * this software and documentation files (the "Software"), including without
 * limitation the rights to use, copy, modify, merge, publish, distribute,
 * sublicense, and/or sell copies of the Software, and to permit persons who
 * receive copies from any such party to do so, with the only requirement being
 * that this copyright notice remain intact.
 */
 
// Ported to Java 12/00 K Weiner
class NeuQuant {
 
  protected static final int netsize = 256; /* number of colours used */
 
  /* four primes near 500 - assume no image has a length so large */
  /* that it is divisible by all four primes */
  protected static final int prime1 = 499;
 
  protected static final int prime2 = 491;
 
  protected static final int prime3 = 487;
 
  protected static final int prime4 = 503;
 
  protected static final int minpicturebytes = (3 * prime4);
 
  /* minimum size for input image */
 
  /*
   * Program Skeleton ---------------- [select samplefac in range 1..30] [read
   * image from input file] pic = (unsigned char*) malloc(3*width*height);
   * initnet(pic,3*width*height,samplefac); learn(); unbiasnet(); [write output
   * image header, using writecolourmap(f)] inxbuild(); write output image using
   * inxsearch(b,g,r)
   */
 
  /*
   * Network Definitions -------------------
   */
 
  protected static final int maxnetpos = (netsize - 1);
 
  protected static final int netbiasshift = 4; /* bias for colour values */
 
  protected static final int ncycles = 100; /* no. of learning cycles */
 
  /* defs for freq and bias */
  protected static final int intbiasshift = 16; /* bias for fractions */
 
  protected static final int intbias = (((int) 1) << intbiasshift);
 
  protected static final int gammashift = 10; /* gamma = 1024 */
 
  protected static final int gamma = (((int) 1) << gammashift);
 
  protected static final int betashift = 10;
 
  protected static final int beta = (intbias >> betashift); /* beta = 1/1024 */
 
  protected static final int betagamma = (intbias << (gammashift - betashift));
 
  /* defs for decreasing radius factor */
  protected static final int initrad = (netsize >> 3); /*
                                                         * for 256 cols, radius
                                                         * starts
                                                         */
 
  protected static final int radiusbiasshift = 6; /* at 32.0 biased by 6 bits */
 
  protected static final int radiusbias = (((int) 1) << radiusbiasshift);
 
  protected static final int initradius = (initrad * radiusbias); /*
                                                                   * and
                                                                   * decreases
                                                                   * by a
                                                                   */
 
  protected static final int radiusdec = 30; /* factor of 1/30 each cycle */
 
  /* defs for decreasing alpha factor */
  protected static final int alphabiasshift = 10; /* alpha starts at 1.0 */
 
  protected static final int initalpha = (((int) 1) << alphabiasshift);
 
  protected int alphadec; /* biased by 10 bits */
 
  /* radbias and alpharadbias used for radpower calculation */
  protected static final int radbiasshift = 8;
 
  protected static final int radbias = (((int) 1) << radbiasshift);
 
  protected static final int alpharadbshift = (alphabiasshift + radbiasshift);
 
  protected static final int alpharadbias = (((int) 1) << alpharadbshift);
 
  /*
   * Types and Global Variables --------------------------
   */
 
  protected byte[] thepicture; /* the input image itself */
 
  protected int lengthcount; /* lengthcount = H*W*3 */
 
  protected int samplefac; /* sampling factor 1..30 */
 
  // typedef int pixel[4]; /* BGRc */
  protected int[][] network; /* the network itself - [netsize][4] */
 
  protected int[] netindex = new int[256];
 
  /* for network lookup - really 256 */
 
  protected int[] bias = new int[netsize];
 
  /* bias and freq arrays for learning */
  protected int[] freq = new int[netsize];
 
  protected int[] radpower = new int[initrad];
 
  /* radpower for precomputation */
 
  /*
   * Initialise network in range (0,0,0) to (255,255,255) and set parameters
   * -----------------------------------------------------------------------
   */
  public NeuQuant(byte[] thepic, int len, int sample) {
 
    int i;
    int[] p;
 
    thepicture = thepic;
    lengthcount = len;
    samplefac = sample;
 
    network = new int[netsize][];
    for (i = 0; i < netsize; i++) {
      network[i] = new int[4];
      p = network[i];
      p[0] = p[1] = p[2] = (i << (netbiasshift + 8)) / netsize;
      freq[i] = intbias / netsize; /* 1/netsize */
      bias[i] = 0;
    }
  }
 
  public byte[] colorMap() {
    byte[] map = new byte[3 * netsize];
    int[] index = new int[netsize];
    for (int i = 0; i < netsize; i++)
      index[network[i][3]] = i;
    int k = 0;
    for (int i = 0; i < netsize; i++) {
      int j = index[i];
      map[k++] = (byte) (network[j][0]);
      map[k++] = (byte) (network[j][1]);
      map[k++] = (byte) (network[j][2]);
    }
    return map;
  }
 
  /*
   * Insertion sort of network and building of netindex[0..255] (to do after
   * unbias)
   * -------------------------------------------------------------------------------
   */
  public void inxbuild() {
 
    int i, j, smallpos, smallval;
    int[] p;
    int[] q;
    int previouscol, startpos;
 
    previouscol = 0;
    startpos = 0;
    for (i = 0; i < netsize; i++) {
      p = network[i];
      smallpos = i;
      smallval = p[1]; /* index on g */
      /* find smallest in i..netsize-1 */
      for (j = i + 1; j < netsize; j++) {
        q = network[j];
        if (q[1] < smallval) { /* index on g */
          smallpos = j;
          smallval = q[1]; /* index on g */
        }
      }
      q = network[smallpos];
      /* swap p (i) and q (smallpos) entries */
      if (i != smallpos) {
        j = q[0];
        q[0] = p[0];
        p[0] = j;
        j = q[1];
        q[1] = p[1];
        p[1] = j;
        j = q[2];
        q[2] = p[2];
        p[2] = j;
        j = q[3];
        q[3] = p[3];
        p[3] = j;
      }
      /* smallval entry is now in position i */
      if (smallval != previouscol) {
        netindex[previouscol] = (startpos + i) >> 1;
        for (j = previouscol + 1; j < smallval; j++)
          netindex[j] = i;
        previouscol = smallval;
        startpos = i;
      }
    }
    netindex[previouscol] = (startpos + maxnetpos) >> 1;
    for (j = previouscol + 1; j < 256; j++)
      netindex[j] = maxnetpos; /* really 256 */
  }
 
  /*
   * Main Learning Loop ------------------
   */
  public void learn() {
 
    int i, j, b, g, r;
    int radius, rad, alpha, step, delta, samplepixels;
    byte[] p;
    int pix, lim;
 
    if (lengthcount < minpicturebytes)
      samplefac = 1;
    alphadec = 30 + ((samplefac - 1) / 3);
    p = thepicture;
    pix = 0;
    lim = lengthcount;
    samplepixels = lengthcount / (3 * samplefac);
    delta = samplepixels / ncycles;
    alpha = initalpha;
    radius = initradius;
 
    rad = radius >> radiusbiasshift;
    if (rad <= 1)
      rad = 0;
    for (i = 0; i < rad; i++)
      radpower[i] = alpha * (((rad * rad - i * i) * radbias) / (rad * rad));
 
    // fprintf(stderr,"beginning 1D learning: initial radius=%d\n", rad);
 
    if (lengthcount < minpicturebytes)
      step = 3;
    else if ((lengthcount % prime1) != 0)
      step = 3 * prime1;
    else {
      if ((lengthcount % prime2) != 0)
        step = 3 * prime2;
      else {
        if ((lengthcount % prime3) != 0)
          step = 3 * prime3;
        else
          step = 3 * prime4;
      }
    }
 
    i = 0;
    while (i < samplepixels) {
      b = (p[pix + 0] & 0xff) << netbiasshift;
      g = (p[pix + 1] & 0xff) << netbiasshift;
      r = (p[pix + 2] & 0xff) << netbiasshift;
      j = contest(b, g, r);
 
      altersingle(alpha, j, b, g, r);
      if (rad != 0)
        alterneigh(rad, j, b, g, r); /* alter neighbours */
 
      pix += step;
      if (pix >= lim)
        pix -= lengthcount;
 
      i++;
      if (delta == 0)
        delta = 1;
      if (i % delta == 0) {
        alpha -= alpha / alphadec;
        radius -= radius / radiusdec;
        rad = radius >> radiusbiasshift;
        if (rad <= 1)
          rad = 0;
        for (j = 0; j < rad; j++)
          radpower[j] = alpha * (((rad * rad - j * j) * radbias) / (rad * rad));
      }
    }
    // fprintf(stderr,"finished 1D learning: final alpha=%f
    // !\n",((float)alpha)/initalpha);
  }
 
  /*
   * Search for BGR values 0..255 (after net is unbiased) and return colour
   * index
   * ----------------------------------------------------------------------------
   */
  public int map(int b, int g, int r) {
 
    int i, j, dist, a, bestd;
    int[] p;
    int best;
 
    bestd = 1000; /* biggest possible dist is 256*3 */
    best = -1;
    i = netindex[g]; /* index on g */
    j = i - 1; /* start at netindex[g] and work outwards */
 
    while ((i < netsize) || (j >= 0)) {
      if (i < netsize) {
        p = network[i];
        dist = p[1] - g; /* inx key */
        if (dist >= bestd)
          i = netsize; /* stop iter */
        else {
          i++;
          if (dist < 0)
            dist = -dist;
          a = p[0] - b;
          if (a < 0)
            a = -a;
          dist += a;
          if (dist < bestd) {
            a = p[2] - r;
            if (a < 0)
              a = -a;
            dist += a;
            if (dist < bestd) {
              bestd = dist;
              best = p[3];
            }
          }
        }
      }
      if (j >= 0) {
        p = network[j];
        dist = g - p[1]; /* inx key - reverse dif */
        if (dist >= bestd)
          j = -1; /* stop iter */
        else {
          j--;
          if (dist < 0)
            dist = -dist;
          a = p[0] - b;
          if (a < 0)
            a = -a;
          dist += a;
          if (dist < bestd) {
            a = p[2] - r;
            if (a < 0)
              a = -a;
            dist += a;
            if (dist < bestd) {
              bestd = dist;
              best = p[3];
            }
          }
        }
      }
    }
    return (best);
  }
 
  public byte[] process() {
    learn();
    unbiasnet();
    inxbuild();
    return colorMap();
  }
 
  /*
   * Unbias network to give byte values 0..255 and record position i to prepare
   * for sort
   * -----------------------------------------------------------------------------------
   */
  public void unbiasnet() {
    for (int i = 0; i < netsize; i++) {
      network[i][0] >>= netbiasshift;
      network[i][1] >>= netbiasshift;
      network[i][2] >>= netbiasshift;
      network[i][3] = i; /* record colour no */
    }
  }
 
  /*
   * Move adjacent neurons by precomputed alpha*(1-((i-j)^2/[r]^2)) in
   * radpower[|i-j|]
   * ---------------------------------------------------------------------------------
   */
  protected void alterneigh(int rad, int i, int b, int g, int r) {
 
    int j, k, lo, hi, a, m;
    int[] p;
 
    lo = i - rad;
    if (lo < -1)
      lo = -1;
    hi = i + rad;
    if (hi > netsize)
      hi = netsize;
 
    j = i + 1;
    k = i - 1;
    m = 1;
    while ((j < hi) || (k > lo)) {
      a = radpower[m++];
      if (j < hi) {
        p = network[j++];
        try {
          p[0] -= (a * (p[0] - b)) / alpharadbias;
          p[1] -= (a * (p[1] - g)) / alpharadbias;
          p[2] -= (a * (p[2] - r)) / alpharadbias;
        } catch (Exception e) {
        } // prevents 1.3 miscompilation
      }
      if (k > lo) {
        p = network[k--];
        try {
          p[0] -= (a * (p[0] - b)) / alpharadbias;
          p[1] -= (a * (p[1] - g)) / alpharadbias;
          p[2] -= (a * (p[2] - r)) / alpharadbias;
        } catch (Exception e) {
        }
      }
    }
  }
 
  /*
   * Move neuron i towards biased (b,g,r) by factor alpha
   * ----------------------------------------------------
   */
  protected void altersingle(int alpha, int i, int b, int g, int r) {
 
    /* alter hit neuron */
    int[] n = network[i];
    n[0] -= (alpha * (n[0] - b)) / initalpha;
    n[1] -= (alpha * (n[1] - g)) / initalpha;
    n[2] -= (alpha * (n[2] - r)) / initalpha;
  }
 
  /*
   * Search for biased BGR values ----------------------------
   */
  protected int contest(int b, int g, int r) {
 
    /* finds closest neuron (min dist) and updates freq */
    /* finds best neuron (min dist-bias) and returns position */
    /* for frequently chosen neurons, freq[i] is high and bias[i] is negative */
    /* bias[i] = gamma*((1/netsize)-freq[i]) */
 
    int i, dist, a, biasdist, betafreq;
    int bestpos, bestbiaspos, bestd, bestbiasd;
    int[] n;
 
    bestd = ~(((int) 1) << 31);
    bestbiasd = bestd;
    bestpos = -1;
    bestbiaspos = bestpos;
 
    for (i = 0; i < netsize; i++) {
      n = network[i];
      dist = n[0] - b;
      if (dist < 0)
        dist = -dist;
      a = n[1] - g;
      if (a < 0)
        a = -a;
      dist += a;
      a = n[2] - r;
      if (a < 0)
        a = -a;
      dist += a;
      if (dist < bestd) {
        bestd = dist;
        bestpos = i;
      }
      biasdist = dist - ((bias[i]) >> (intbiasshift - netbiasshift));
      if (biasdist < bestbiasd) {
        bestbiasd = biasdist;
        bestbiaspos = i;
      }
      betafreq = (freq[i] >> betashift);
      freq[i] -= betafreq;
      bias[i] += (betafreq << gammashift);
    }
    freq[bestpos] += beta;
    bias[bestpos] -= betagamma;
    return (bestbiaspos);
  }
}